The null hypothesis is that degree of anticoagulation (as assessed by ACT) has not relation with RAO. Alternative hypothesis is that incidence of RAO varies according to ACT values. Assuming a 6% of incidence of RAO at 24 hours, 95% confidence intervals would be 5% to 7% for a 2168-patient sample (110-151); PCIs must be at least 50% of the procedures, and enrollment should not stopped until at least 110 primary events (RAO) have occurred. An-interim analysis at 1084 patients enrolled will be performed. This sample size should allow evaluation of correlation of ACT with RAO both as continuous and ordinal variable. A statistical model (non-linear regression) will be fitted to the relation between RAO and ACT values. Receiver-operating characteristic (ROC) cut-off values will be obtained according to the best compromise between sensitivity and specificity, and a threshold effect will be investigated. To adjust for confounders, multivariate logistic regression analysis will be performed, considering the presence of RAO as dependent variable. In addition to ACT values (setting the group with lowest incidence as reference), other 4 variables known to be related with RAO will be entered into the model (heparin dosage, postprocedural compression time, patent hemostasis, sheath size) and odds ratios with 95% confidence intervals will be calculated. An exploratory analysis regarding possible role of other variables (sex, spasmolytic drugs, procedural time, multiple procedures, hemostasis device, pressure before sheath removal, antiGP IIb/IIIa drugs) will be performed. Pre-planned analysis of RAO incidence according to ACT values will be performed in these subgroups: patients who underwent coronary angiography vs patients who underwent PCI, patients in whom patent hemostasis was possible vs patients in whom patent hemostasis was not possible, patients with acute coronary syndrome vs without. Kaplan-Meier curves of MACCEs within 12 months after procedures according to RAO occurence will be plot and compared using log-rank statistics and Cox regression, adjusting for age, acute coronary syndrome and diabetes. Normality of data distribution will be assessed by skewness and kurtosis and by linear plot graph. Data will be reported as mean±standard deviation or median and interquartile range according to distribution. Chi-squared statistics will be used for categorical variables, and the t-test or Mann-Whitney U test for scale variables if data followed normal or non-normal distribution, respectively. Post-test Bonferroni correction and Dunn's test will be used for pairwise comparisons among groups. Statistical significance will be set at p<0.05 (two-tailed) for all tests. All data will be analysed using Prism (version 5, Graphpad, California) or SPSS software (version 20.0; SPSS Inc., Chicago, IL, USA).